QFO-UCNN: Quantizable Feature Oriented Utilitarian Convolutional Neural Network for Sar Recognition
Author:
Affiliation:
1. Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China,Tianjin,China,300300
2. State Grid Cyber Security Technology (Beijing) CO., LTD,Beijing,China,102200
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10389812/10388494/10390781.pdf?arnumber=10390781
Reference16 articles.
1. A Keystone Transform Without Interpolation for SAR Ground Moving-Target Imaging
2. Measuring Ionospheric Scintillation Parameters From SAR Images Using Phase Gradient Autofocus: A Case Study
3. GuidedNet: A General CNN Fusion Framework via High-Resolution Guidance for Hyperspectral Image Super-Resolution
4. Free-Weight Exercise Activity Recognition using Deep Residual Neural Network based on Sensor Data from In-Ear Wearable Devices
5. A CNN-Based Self-Supervised Synthetic Aperture Radar Image Denoising Approach
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